supported in part by STI 2030-Major Projects under Grant 2022ZD0209200;in part by Beijing Natural Science Foundation-Xiaomi Innovation Joint Fund(L233009);in part by National Natural Science Foundation of China under Grant No.62374099;in part by the Tsinghua-Toyota Joint Research Fund;in part by the Daikin Tsinghua Union Program;in part by Independent Research Program of School of Integrated Circuits,Tsinghua University;This work was also sponsored by CIE-Tencent Robotics X Rhino-Bird Focused Research Program.
Emerging two-dimensional(2D)semiconductors are among the most promising materials for ultra-scaled transistors due to their intrinsic atomic-level thickness.As the stacking process advances,the complexity and cost of ...
supported by the Project of China Southern Power Grid Digital Grid Research Institute Co.,Ltd.(210002KK52222026)。
By modeling the spatiotemporal data of the power grid, it is possible to better understand its operational status, identify potential issues and risks, and take timely measures to adjust and optimize the system. Compa...
Research Committee,National Technical University of Athens。
In this study,the design and development of a sensor made of low-cost parts to monitor inclination and acceleration are presented.Αmicro electro-mechanical systems,micro electro mechanical systems,sensor was housed i...
supported by grants from the National Natural Science Foundation of China(82373859);the China Postdoctoral Science Foundation(2023M743145).
Ablation of seizure foci represents a crucial therapeutic approach for epilepsy.Traditionally,the seizure foci are predominantly located in the anterior hippocampus and amygdala.However,recent research by Ivan Soltesz...
supported in part by National Key Research and Development Program of China(Grant No.2022YFF0712300);National Natural Science Foundation of China(Grant No.62172177);Knowledge Innovation Program of Wuhan-Shuguang;Fundamental Research Funds for the Central Universities(HUST)(Grant No.2022JYCXJJ034);Open Research Fund from Shandong Provincial Key Laboratory of Computer Network(Grant No.SKLCN-2021-02)。
In recent years,unsupervised multiplex graph representation learning(UMGRL)has received increasing research interest,which aims to learn discriminative node features from the multiplex graphs supervised by data withou...
supported by the National Natural Science Foundation of China(Grant Nos.62141214 and 62272171).
Classic Graph Convolutional Networks (GCNs) often learn node representation holistically, which ignores the distinct impacts from different neighbors when aggregating their features to update a node’s representation....